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Learn · Computational Neuroscience

Lecture 4 of 60Week 1

Lecture 04 : Systems of neural processing

Prof. Sharba Bandyopadhyay · IIT Kharagpur

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From
Computational Neuroscience, IIT Kharagpur (at NPTEL)
Licence
CC BY-NC-SA, as NPTEL states it. Non-commercial use only.
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NPTEL states: "Distributed under Creative Commons Attribution-ShareAlike / CC BY - NC - SA", beside a BY-NC-SA badge.
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All the lectures

  1. Lecture 01 : Neuron structure YouTube
  2. Lecture 02 : Networks of Neurons and Synapses YouTube
  3. Lecture 03 : Basic Structures in the Brain YouTube
  4. Lecture 04 : Systems of neural processing YouTube
  5. Lecture 05 : Methods of Recording Neural Activity YouTube
  6. Lecture 06 : Membrane Potential and All or None Spike YouTube
  7. Lecture 07 : Patch Clamp Measurements YouTube
  8. Lecture 08 : Ion channels YouTube
  9. Lecture 09 : Current injection: Synapses YouTube
  10. Lecture 10 : Single Neuron Activity YouTube
  11. Lecture 11 : Point and compartmental models of neurons YouTube
  12. Lecture 12 : Hodgkin Huxley Equations - I YouTube
  13. Lecture 13 : Hodgkin Huxley Equations – II YouTube
  14. Lecture 14 : Reducing the HHE and Moris-Lecar Equations (MLE) YouTube
  15. Lecture 15 : Properties of MLE YouTube
  16. Lecture 16 : Phase Plane Analysis - I YouTube
  17. Lecture 17 : Phase Plane Analysis - II YouTube
  18. Lecture 18 : Phase Plane Analysis - III YouTube
  19. Lecture 19 : Analyzing HHE with Phase Plane Analysis -I YouTube
  20. Lecture 20 : Analyzing HHE with Phase Plane Analysis -II YouTube
  21. Lecture 21 : Random variables and random process YouTube
  22. Lecture 22 : Spike train statistics and response measure YouTube
  23. Lecture 23 : Receptive fields and models of receptive fields YouTube
  24. Lecture 24 : Stimulus to Response mapping(Coding) - I YouTube
  25. Lecture 25 : Stimulus to Response mapping(Coding) - II YouTube
  26. Lecture 26: Stimulus to Response Mapping(Coding) - III YouTube
  27. Lecture 27: Response to Stimulus Mapping (Decoding) YouTube
  28. Lecture 28: Basics of Information Theory - I YouTube
  29. Lecture 29: Basics of Information Theory - II YouTube
  30. Lecture 30: Maximally Informative Dimensions YouTube
  31. Lecture 31 : Intro to Discrimination based methods YouTube
  32. Lecture 32 : Kullback Leibler Distance YouTube
  33. Lecture 33 : Measuring Spike Train Distances - I YouTube
  34. Lecture 34 : Measuring Spike Train Distances - II YouTube
  35. Lecture 35 : Signal and Noise Correlations YouTube
  36. Lecture 36: Statistical Methods in Discrimination YouTube
  37. Lecture 37: Single Cell Decoding - I: Two Alternative Forced Choice task in Monkeys YouTube
  38. Lecture 38: Single Cell Decoding - II: Using ROC Curves for discrimination YouTube
  39. Lecture 39: Single Cell Encoding - I: Operant Conditioning Task in Ferrets YouTube
  40. Lecture 40: Single Cell Encoding - II: Learning in avoidance and approach methods in Ferrets YouTube
  41. Lecture 41: Plasticity - Synaptic Transmission and Synaptic Strength YouTube
  42. Lecture 42: Ways of modification of Synaptic Strength YouTube
  43. Lecture 43: Type of Plasticity YouTube
  44. Lecture 44: Short Term Plasticity - I YouTube
  45. Lecture 45: Short Term Plasticity - II YouTube
  46. Lecture 46 : Long Term Plasticity YouTube
  47. Lecture 47 : Spike Time Dependent Plasticity YouTube
  48. Lecture 48 : Hebbian Plasticity YouTube
  49. Lecture 49 : BCM Rule YouTube
  50. Lecture 50 : Synaptic Normalization YouTube
  51. Lecture 51 : Adaptation YouTube
  52. Lecture 52 : Models of Short Term Plasticity YouTube
  53. Lecture 53 : Attention - I YouTube
  54. Lecture 54 : Attention - II YouTube
  55. Lecture 55 : Developmental Cicuits YouTube
  56. Lecture 56 : Optimal Coding in Visual System YouTube
  57. Lecture 57 : Optimal Coding in Auditory System YouTube
  58. Lecture 58 : Optimal Coding of Deviant Stimuli in Development YouTube
  59. Lecture 59 : Spike Timing Dependent Plasticity - a theoretical Perspective YouTube
  60. Lecture 60 : Important Problems in Neuroscience YouTube